scholarly journals Geographical Aspects of Recent Trends in Drug-Related Deaths, with a Focus on Intra-National Contextual Variation

2020 ◽  
Vol 17 (21) ◽  
pp. 8081
Author(s):  
Peter Congdon
Keyword(s):  
Small Area ◽  
Drug Misuse ◽  
Individual Risk ◽  
Mortality Data ◽  
Death Rates ◽  
Drug Deaths ◽  
National Differences ◽  
The Us ◽  
Drug Death ◽  
The Impact

Background. Recent worldwide estimates are of 53 million users of opioids annually, and of 585,000 drug-related deaths, of which two thirds are due to opioids. There are considerable international differences in levels of drug death rates and substance abuse. However, there are also considerable variations within countries in drug misuse, overdose rates, and in drug death rates particularly. Wide intra-national variations characterize countries where drug deaths have risen fastest in recent years, such as the US and UK. Drug deaths are an outcome of drug misuse, which can ideally be studied at a relatively low spatial scale (e.g., US counties). The research literature suggests that small area variations in drug deaths to a considerable degree reflect contextual (place-related) factors as well as individual risk factors. Methods. We consider the role of area social status, social cohesion, segregation, urbanicity, and drug supply in an ecological regression analysis of county differences in drug deaths in the US during 2015–2017. Results. The analysis of US small area data highlights a range of factors which are statistically significant in explaining differences in drug deaths, but with no risk factor having a predominant role. Comparisons with other countries where small area drug mortality data have been analyzed show differences between countries in the impact of different contextual factors, but some common themes. Conclusions. Intra-national differences in drug-related deaths are considerable, but there are significant research gaps in the evidence base for small area analysis of such deaths.

De-unionization and Drug Death Rates

2018 ◽  
Vol 6 (1) ◽  
pp. 4-13 ◽  
Author(s):  
Robert DeFina ◽  
Lance Hannon
Keyword(s):  
Fixed Effects ◽  
Union Density ◽  
The United States ◽  
Sociological Research ◽  
Social Forces ◽  
Death Rates ◽  
Drug Deaths ◽  
Drug Death ◽  
The Relationship ◽  
Institutional Decline

Drug death rates in the United States have risen dramatically in recent years, sparking urgent discussions about causes. Most of these discussions have centered on supply-side issues, such as doctors overprescribing pain killers. However, there is increasing recognition of the need to go beyond proximate causes and to consider larger social forces that bear on the demand for pain-relieving drugs. Informed by sociological research linking labor unions to community health, we empirically examined the relationship between union density and drug death rates for the years 1999 to 2016. We found that states experiencing greater declines in unionization also tended to experience greater increases in drug deaths. Estimates from our fixed-effects models suggested that a one standard deviation decrease in union density was associated with a 42 percent increase in drug death rates over the period. Although the incorporation of a variety of statistical controls reduced this association, it remained negative and significant. Beyond variation in the availability of substances to misuse, our findings underscore the importance of considering institutional decline and broader social conditions as deeply relevant for contemporary drug death trends.

scholarly journals US life expectancy stalls due to cardiovascular disease, not drug deaths

2020 ◽  
Vol 117 (13) ◽  
pp. 6998-7000 ◽  
Author(s):  
Neil K. Mehta ◽  
Leah R. Abrams ◽  
Mikko Myrskylä
Keyword(s):  
Cardiovascular Disease ◽  
Life Expectancy ◽  
Drug Overdose ◽  
Causes Of Death ◽  
High Income ◽  
Death Rates ◽  
Drug Deaths ◽  
The Us ◽  
Main Culprit ◽  
Cvd Mortality

After decades of robust growth, the rise in US life expectancy stalled after 2010. Explanations for the stall have focused on rising drug-related deaths. Here we show that a stagnating decline in cardiovascular disease (CVD) mortality was the main culprit, outpacing and overshadowing the effects of all other causes of death. The CVD stagnation held back the increase of US life expectancy at age 25 y by 1.14 y in women and men, between 2010 and 2017. Rising drug-related deaths had a much smaller effect: 0.1 y in women and 0.4 y in men. Comparisons with other high-income countries reveal that the US CVD stagnation is unusually strong, contributing to a stark mortality divergence between the US and peer nations. Without the aid of CVD mortality declines, future US life expectancy gains must come from other causes—a monumental task given the enormity of earlier declines in CVD death rates. Reversal of the drug overdose epidemic will be beneficial, but insufficient for achieving pre-2010 pace of life expectancy growth.

Abstract P180: Impact of Intensive Systolic Blood Pressure Treatment on Cardiovascular Disease and Mortality in the US Population

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Joshua D Bundy ◽  
Changwei Li ◽  
Jiang He
Keyword(s):  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Clinical Trials ◽  
Systolic Blood Pressure ◽  
Incidence Rates ◽  
Intensive Treatment ◽  
Baseline Risk ◽  
Mortality Data ◽  
The Us ◽  
The Impact

Introduction: Hypertension is the most important risk factor for cardiovascular disease (CVD), the leading cause of morbidity and mortality among US adults. Clinical trials suggest that intensive systolic blood pressure (BP) management significantly reduces risk of CVD and mortality in patients at high risk for CVD. However, the impact of intensive BP lowering in the US population is uncertain. Hypothesis: More intensive treatment of systolic BP provides great benefits in the reduction of CVD and total deaths in the US population aged ≥40 years. Methods: We pooled follow-up data in 31,851 individuals from four US cohort studies (ARIC, CHS, Framingham Heart Study, and MESA) to estimate annual incidence rates of major CVD (combined stroke, coronary heart disease, and heart failure) by sex, race (white and non-white), and age groups (40-49, 50-59, 60-69, and ≥70 years). We retrieved mortality data from annual death statistics reported by the CDC. We combined nationally-representative survey data from three NHANES cycles (2009-2010, 2011-2012, 2013-2014) to estimate the proportions of US adults aged ≥40 years in each of 10 systolic BP categories (range <120 to ≥160 mm Hg). A Bayesian network meta-analysis of antihypertensive clinical trials was used to estimate relative risks for CVD and mortality comparing each of the 10 systolic BP categories, after adjusting for baseline risk in included trials. Using these data sources, we calculated the population attributable fractions and number of events (and deaths) that could be reduced by treating systolic BP ≥140 mmHg to more intensive systolic BP targets in the US population. Results: Treating systolic BP to 120-124 mm Hg showed the largest reduction in number of CVD events and total deaths compared to higher targets (Table). Conclusions: In conclusion, intensive treatment of systolic BP could prevent a large number of CVD events and total deaths in the US population.

scholarly journals Impact of diet on health and longevity in London 1850–1880

JRSM Open ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 205427042096953
Author(s):  
Peter Greaves
Keyword(s):  
Water Supply ◽  
Great Difficulty ◽  
Living Condition ◽  
Polluted Water ◽  
Mortality Data ◽  
Gastrointestinal Infections ◽  
Death Rates ◽  
High Death Rate ◽  
High Death ◽  
The Impact

This study examines the impact of diet on health in different districts of mid-19th century London. Surveys of London diets and living condition were compared with mortality data between 1851 and 1880. Despite an abundance of fresh foods reaching London, the very poor labouring population living in the inner boroughs between 1850 and 1861 had great difficulty obtaining sufficient nourishment because of its cost. This population showed high death rates from infectious diseases, notably pulmonary tuberculosis, which was endemic and is typically associated with poor nutrition. This high death rate was exacerbated by more deaths from gastrointestinal infections associated with a polluted water supply from the river Thames. By contrast, the poor in the outer suburbs enjoyed both more nutritious diets and cleaner water which was associated with lower death rates comparable to those in rural Britain. Outer suburbs retained a relatively rural life-style associated with cleaner water and an abundance of locally grown food. In the following two decades, there was a significant reduction in the death rates from gastrointestinal infections in the inner boroughs which correlated with the major improvements in London’s water supply. The decline in death rates from tuberculosis and other infectious disease was inconsistent and increased in some boroughs, suggesting patchy economic improvement and a persisting limited ability of many of London’s poor to afford a nutritious diet.

scholarly journals Predicting County-Level Overdose Death Rates Amid the Escalating Overdose Crisis in the United States: A Statistical Modeling Approach Predicting Deaths Through 2022

2022 ◽  
Author(s):  
Charles Marks ◽  
Daniela Abramowitz ◽  
Christl A. Donnelly ◽  
Daniel Ciccarone ◽  
Natasha Martin ◽  
...  
Keyword(s):  
Negative Binomial ◽  
The United States ◽  
Similar Efficacy ◽  
Original Model ◽  
Mortality Data ◽  
County Level ◽  
Online Application ◽  
Death Rates ◽  
Overdose Death ◽  
The Us

Aims. U.S. overdose (OD) deaths continue to escalate but are characterized by geographic and temporal heterogeneity. We previously validated a predictive statistical model to predict county-level OD mortality nationally from 2013 to 2018. Herein, we aimed to: 1) validate our model’s performance at predicting county-level OD mortality in 2019 and 2020; 2) modify and validate our model to predict OD mortality in 2022.Methods. We evaluated our mixed effects negative binomial model’s performance at predicting county-level OD mortality in 2019 and 2020. Further, we modified our model which originally used data from the year X to predict OD deaths in the year X+1 to instead predict deaths in year X+3. We validated this modification for the years 2017 through 2019 and generated future-oriented predictions for 2022. Finally, to leverage available, albeit incomplete, 2020 OD mortality data, we also modified and validated our model to predict OD deaths in year X+2 and generated an alternative set of predictions for 2022.Results. Our original model continued to perform with similar efficacy in 2019 and 2020, remaining superior to a benchmark approach. Our modified X+3 model performed with similar efficacy as our original model, and we present predictions for 2022, including identification of counties most likely to experience highest OD mortality rates. There was a high correlation (Spearman’s ρ = 0.93) between the rank ordering of counties for our 2022 predictions using our X+3 and X+2 models. However, the X+3 model (which did not account for OD escalation during COVID) predicted only 62,000 deaths nationwide for 2022, whereas the X+2 model predicted over 87,000.Conclusion. We have predicted county-level overdose death rates for 2022 across the US. These predictions, made publicly available in our online application, can be used to identify counties at highest risk of high OD mortality and support evidence-based OD prevention planning.

scholarly journals Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260381
Author(s):  
Iain M. Carey ◽  
Derek G. Cook ◽  
Tess Harris ◽  
Stephen DeWilde ◽  
Umar A. R. Chaudhry ◽  
...  
Keyword(s):  
Risk Factors ◽  
Primary Care ◽  
Excess Mortality ◽  
Total Mortality ◽  
Individual Risk ◽  
Mortality Data ◽  
All Cause Mortality ◽  
Specific Mortality ◽  
Mortality Ratio ◽  
The Impact

Background The COVID-19 pandemic’s first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period. Objective To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015–19. Methods Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30–104 years, for each year between 18-March and 19-May over a 6-year period (2015–2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015–19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015–19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR). Results RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97–3.18; compared to UMR = 0.92, 95%CI 0.85–1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65–0.98) compared to its UMR = 1.64. Conclusions Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic’s impact by individual risk factor without requiring cause-specific mortality data.

scholarly journals Will Vaccine-derived Protective Immunity Curtail COVID-19 Variants in the US?

2021 ◽  
Author(s):  
Marina Mancuso ◽  
Steffen Eikenberry ◽  
Abba Gumel
Keyword(s):  
Vaccine Coverage ◽  
Protective Efficacy ◽  
Wild Strain ◽  
The United States ◽  
Cross Protection ◽  
Mortality Data ◽  
High Coverage ◽  
New Variant ◽  
The Us ◽  
The Impact

Multiple effective vaccines are currently being deployed to combat the COVID-19 pandemic (caused by SARS-COV-2), and are viewed as the major factor in marked reductions in disease burden in regions around the world with moderate to high coverage of these vaccines. The effectiveness of COVID-19 vaccination programs is, however, significantly threatened by the emergence of new SARS-COV-2 variants that, in addition to being more transmissible and potentially more virulent than the wild (resident) strain, may at least partially evade existing vaccines. A new two-strain (one resident, the other wild) and two-group (vaccinated or otherwise) mechanistic mathematical model is designed and used to assess the impact of the vaccine-induced cross-protective efficacy on the spread the COVID-19 pandemic in the United States. Analysis of the model, which is fitted using COVID-19 mortality data for the US, shows that vaccine-induced herd immunity can be achieved if 61% of the American population is fully vaccinated with the Pfizer or Moderna vaccines. Parameter sensitivity analysis suggests three main factors that significantly affect the COVID-19 burden in the US, namely (a) daily vaccination rate, (b) the level of cross-protection the vaccines offer against the variant, and (c) the relative infectiousness of the dominant variant relative to the wild strain. This study further suggests that a new variant can cause a significant disease surge in the US if (i) the vaccine coverage against the wild strain is low (roughly < 50%), (ii) the variant is much more transmissible (e.g., twice more transmissible) than the wild-type strain, or (iii) the level of cross-protection offered by the vaccine is relatively low (e.g., less than 70%). A new variant will not cause such surge in the US if it is only moderately more transmissible (e.g., 1:56 more transmissible) than the wild strain, at least 66% of the population of the US is fully vaccinated, and the three vaccines being deployed in the US (Pfizer, Moderna, and Johnson & Johnson) offer a moderate level of cross-protection against the variant.

Assessing the Impact of Suicide Exclusion Periods on Life Insurance

Crisis ◽  
2010 ◽  
Vol 31 (4) ◽  
pp. 217-223 ◽  
Author(s):  
Paul Yip ◽  
David Pitt ◽  
Yan Wang ◽  
Xueyuan Wu ◽  
Ray Watson ◽  
...  
Keyword(s):  
Life Insurance ◽  
Accidental Death ◽  
Insurance Policy ◽  
Death Rates ◽  
Insurance Policies ◽  
Suicidal Death ◽  
Insured Individual ◽  
The Impact ◽  
Insurance Data ◽  
The Relationship

Background: We study the impact of suicide-exclusion periods, common in life insurance policies in Australia, on suicide and accidental death rates for life-insured individuals. If a life-insured individual dies by suicide during the period of suicide exclusion, commonly 13 months, the sum insured is not paid. Aims: We examine whether a suicide-exclusion period affects the timing of suicides. We also analyze whether accidental deaths are more prevalent during the suicide-exclusion period as life-insured individuals disguise their death by suicide. We assess the relationship between the insured sum and suicidal death rates. Methods: Crude and age-standardized rates of suicide, accidental death, and overall death, split by duration since the insured first bought their insurance policy, were computed. Results: There were significantly fewer suicides and no significant spike in the number of accidental deaths in the exclusion period for Australian life insurance data. More suicides, however, were detected for the first 2 years after the exclusion period. Higher insured sums are associated with higher rates of suicide. Conclusions: Adverse selection in Australian life insurance is exacerbated by including a suicide-exclusion period. Extension of the suicide-exclusion period to 3 years may prevent some “insurance-induced” suicides – a rationale for this conclusion is given.

Systematic review methodology for development: An example from microfinance

2018 ◽  
Vol 43 (1) ◽  
pp. 65-77 ◽  
Author(s):  
Carina Van Rooyen ◽  
Ruth Stewart ◽  
Thea De Wet
Keyword(s):  
Systematic Review ◽  
International Development ◽  
Health Sector ◽  
Evidence Based ◽  
Systematic Review Methodology ◽  
Development Interventions ◽  
The Us ◽  
Sub Saharan ◽  
The Impact ◽  
Evidence Based Decision Making

Big international development donors such as the UK’s Department for International Development and USAID have recently started using systematic review as a methodology to assess the effectiveness of various development interventions to help them decide what is the ‘best’ intervention to spend money on. Such an approach to evidence-based decision-making has long been practiced in the health sector in the US, UK, and elsewhere but it is relatively new in the development field. In this article we use the case of a systematic review of the impact of microfinance on the poor in sub-Saharan African to indicate how systematic review as a methodology can be used to assess the impact of specific development interventions.

The Impact of Monetary and Fiscal Policies on the Stock Market in the United States (U.S); Evidence from Linear ARDL Framework

2020 ◽  
Vol 11 (1) ◽  
pp. 132-132
Author(s):  
Aref Emamian
Keyword(s):  
United States ◽  
Stock Market ◽  
The United States ◽  
Real Effective Exchange Rate ◽  
Annual Data ◽  
Fiscal Policies ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
The Impact

This study examines the impact of monetary and fiscal policies on the stock market in the United States (US), were used. By employing the method of Autoregressive Distributed Lags (ARDL) developed by Pesaran et al. (2001). Annual data from the Federal Reserve, World Bank, and International Monetary Fund, from 1986 to 2017 pertaining to the American economy, the results show that both policies play a significant role in the stock market. We find a significant positive effect of real Gross Domestic Product and the interest rate on the US stock market in the long run and significant negative relationship effect of Consumer Price Index (CPI) and broad money on the US stock market both in the short run and long run. On the other hand, this study only could support the significant positive impact of tax revenue and significant negative impact of real effective exchange rate on the US stock market in the short run while in the long run are insignificant. Keywords: ARDL, monetary policy, fiscal policy, stock market, United States

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